@inproceedings{toledo-etal-2014-towards,
title = "Towards a Semantic Model for Textual Entailment Annotation",
author = "Toledo, Assaf and
Alexandropoulou, Stavroula and
Chesney, Sophie and
Katrenko, Sophia and
Klockmann, Heid and
Kokke, Pepjin and
Kruit, Benno and
Winter, Yoad",
booktitle = "Linguistic Issues in Language Technology, Volume 9, 2014 - Perspectives on Semantic Representations for Textual Inference",
year = "2014",
publisher = "CSLI Publications",
url = "https://aclanthology.org/2014.lilt-9.10",
abstract = "We introduce a new formal semantic model for annotating textual entailments that describes restrictive, intersective, and appositive modification. The model contains a formally defined interpreted lexicon, which specifies the inventory of symbols and the supported semantic operators, and an informally defined annotation scheme that instructs annotators in which way to bind words and constructions from a given pair of premise and hypothesis to the interpreted lexicon. We explore the applicability of the proposed model to the Recognizing Textual Entailment (RTE) 1{--}4 corpora and describe a first-stage annotation scheme on which we based the manual annotation work. The constructions we annotated were found to occur in 80.65{\%} of the entailments in RTE 1{--}4 and were annotated with cross-annotator agreement of 68{\%} on average. The annotated parts of the RTE corpora are publicly available for further research.",
}
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<abstract>We introduce a new formal semantic model for annotating textual entailments that describes restrictive, intersective, and appositive modification. The model contains a formally defined interpreted lexicon, which specifies the inventory of symbols and the supported semantic operators, and an informally defined annotation scheme that instructs annotators in which way to bind words and constructions from a given pair of premise and hypothesis to the interpreted lexicon. We explore the applicability of the proposed model to the Recognizing Textual Entailment (RTE) 1–4 corpora and describe a first-stage annotation scheme on which we based the manual annotation work. The constructions we annotated were found to occur in 80.65% of the entailments in RTE 1–4 and were annotated with cross-annotator agreement of 68% on average. The annotated parts of the RTE corpora are publicly available for further research.</abstract>
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%0 Conference Proceedings
%T Towards a Semantic Model for Textual Entailment Annotation
%A Toledo, Assaf
%A Alexandropoulou, Stavroula
%A Chesney, Sophie
%A Katrenko, Sophia
%A Klockmann, Heid
%A Kokke, Pepjin
%A Kruit, Benno
%A Winter, Yoad
%S Linguistic Issues in Language Technology, Volume 9, 2014 - Perspectives on Semantic Representations for Textual Inference
%D 2014
%I CSLI Publications
%F toledo-etal-2014-towards
%X We introduce a new formal semantic model for annotating textual entailments that describes restrictive, intersective, and appositive modification. The model contains a formally defined interpreted lexicon, which specifies the inventory of symbols and the supported semantic operators, and an informally defined annotation scheme that instructs annotators in which way to bind words and constructions from a given pair of premise and hypothesis to the interpreted lexicon. We explore the applicability of the proposed model to the Recognizing Textual Entailment (RTE) 1–4 corpora and describe a first-stage annotation scheme on which we based the manual annotation work. The constructions we annotated were found to occur in 80.65% of the entailments in RTE 1–4 and were annotated with cross-annotator agreement of 68% on average. The annotated parts of the RTE corpora are publicly available for further research.
%U https://aclanthology.org/2014.lilt-9.10
Markdown (Informal)
[Towards a Semantic Model for Textual Entailment Annotation](https://aclanthology.org/2014.lilt-9.10) (Toledo et al., LILT 2014)
ACL
- Assaf Toledo, Stavroula Alexandropoulou, Sophie Chesney, Sophia Katrenko, Heid Klockmann, Pepjin Kokke, Benno Kruit, and Yoad Winter. 2014. Towards a Semantic Model for Textual Entailment Annotation. In Linguistic Issues in Language Technology, Volume 9, 2014 - Perspectives on Semantic Representations for Textual Inference. CSLI Publications.